{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# K-Means Clustering in Python -- Synthetic Data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This jupyter notebook accompanies the Real Python's [Practical K-Means Clustering in Python](https://realpython.com/practical-k-means-clustering-python/) article. Specifically, this notebook works through the **first half** of the article, when working with synthetic data."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## K-Means Clustering in Python"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "from kneed import KneeLocator\n",
    "from sklearn.cluster import KMeans\n",
    "from sklearn.datasets import make_blobs\n",
    "from sklearn.metrics import silhouette_score\n",
    "from sklearn.preprocessing import StandardScaler"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "features, true_labels = make_blobs(\n",
    "    n_samples=200, centers=3, cluster_std=2.75, random_state=42\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[  9.77075874,   3.27621022],\n",
       "       [ -9.71349666,  11.27451802],\n",
       "       [ -6.91330582,  -9.34755911],\n",
       "       [-10.86185913, -10.75063497],\n",
       "       [ -8.50038027,  -4.54370383]])"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "features[:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1, 0, 2, 2, 2])"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "true_labels[:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "scaler = StandardScaler()\n",
    "scaled_features = scaler.fit_transform(features)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 2.13082109,  0.25604351],\n",
       "       [-1.52698523,  1.41036744],\n",
       "       [-1.00130152, -1.56583175],\n",
       "       [-1.74256891, -1.76832509],\n",
       "       [-1.29924521, -0.87253446]])"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "scaled_features[:5]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "kmeans = KMeans(\n",
    "    init=\"random\", n_clusters=3, n_init=10, max_iter=300, random_state=42\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "KMeans(init='random', n_clusters=3, random_state=42)"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "kmeans.fit(scaled_features)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "74.57960106819854"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# The lowest SSE value\n",
    "kmeans.inertia_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 1.19539276,  0.13158148],\n",
       "       [-0.25813925,  1.05589975],\n",
       "       [-0.91941183, -1.18551732]])"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Final locations of the centroid\n",
    "kmeans.cluster_centers_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "6"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# The number of iterations required to converge\n",
    "kmeans.n_iter_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0, 1, 2, 2, 2], dtype=int32)"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "kmeans.labels_[:5]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### How to Choose the Number of Clusters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "kmeans_kwargs = {\n",
    "    \"init\": \"random\",\n",
    "    \"n_init\": 10,\n",
    "    \"max_iter\": 300,\n",
    "    \"random_state\": 42,\n",
    "}\n",
    "\n",
    "# A list holds the SSE values for each k\n",
    "sse = []\n",
    "for k in range(1, 11):\n",
    "    kmeans = KMeans(n_clusters=k, **kmeans_kwargs)\n",
    "    kmeans.fit(scaled_features)\n",
    "    sse.append(kmeans.inertia_)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.style.use(\"fivethirtyeight\")\n",
    "plt.plot(range(1, 11), sse)\n",
    "plt.xticks(range(1, 11))\n",
    "plt.xlabel(\"Number of Clusters\")\n",
    "plt.ylabel(\"SSE\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "kl = KneeLocator(range(1, 11), sse, curve=\"convex\", direction=\"decreasing\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "kl.elbow"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "# A list holds the silhouette coefficients for each k\n",
    "silhouette_coefficients = []\n",
    "\n",
    "# Notice we start at 2 clusters for silhouette coefficient\n",
    "for k in range(2, 11):\n",
    "    kmeans = KMeans(n_clusters=k, **kmeans_kwargs)\n",
    "    kmeans.fit(scaled_features)\n",
    "    score = silhouette_score(scaled_features, kmeans.labels_)\n",
    "    silhouette_coefficients.append(score)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.style.use(\"fivethirtyeight\")\n",
    "plt.plot(range(2, 11), silhouette_coefficients)\n",
    "plt.xticks(range(2, 11))\n",
    "plt.xlabel(\"Number of Clusters\")\n",
    "plt.ylabel(\"Silhouette Coefficient\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Advanced Clustering Evaluation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "from sklearn.cluster import DBSCAN\n",
    "from sklearn.datasets import make_moons\n",
    "from sklearn.metrics import adjusted_rand_score"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "features, true_labels = make_moons(n_samples=250, noise=0.05, random_state=42)\n",
    "scaled_features = scaler.fit_transform(features)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Instantiate k-means and dbscan algorithms\n",
    "kmeans = KMeans(n_clusters=2)\n",
    "dbscan = DBSCAN(eps=0.3)\n",
    "\n",
    "# Fit the algorithms to the features\n",
    "kmeans.fit(scaled_features)\n",
    "dbscan.fit(scaled_features)\n",
    "\n",
    "# Compute the silhouette scores for each algorithm\n",
    "kmeans_silhouette = silhouette_score(scaled_features, kmeans.labels_).round(2)\n",
    "dbscan_silhouette = silhouette_score(scaled_features, dbscan.labels_).round(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.5"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "kmeans_silhouette"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.38"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dbscan_silhouette"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 576x432 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot the data and cluster silhouette comparison\n",
    "fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(8, 6), sharex=True, sharey=True)\n",
    "fig.suptitle(\"Clustering Algorithm Comparison: Crescents\", fontsize=16)\n",
    "fte_colors = {\n",
    "    0: \"#008fd5\",\n",
    "    1: \"#fc4f30\",\n",
    "}\n",
    "# The k-means plot\n",
    "km_colors = [fte_colors[label] for label in kmeans.labels_]\n",
    "ax1.scatter(scaled_features[:, 0], scaled_features[:, 1], c=km_colors)\n",
    "ax1.set_title(\n",
    "    f\"k-means\\nSilhouette: {kmeans_silhouette}\", fontdict={\"fontsize\": 12}\n",
    ")\n",
    "\n",
    "# The dbscan plot\n",
    "db_colors = [fte_colors[label] for label in dbscan.labels_]\n",
    "ax2.scatter(scaled_features[:, 0], scaled_features[:, 1], c=db_colors)\n",
    "ax2.set_title(\n",
    "    f\"DBSCAN\\nSilhouette: {dbscan_silhouette}\", fontdict={\"fontsize\": 12}\n",
    ")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "ari_kmeans = adjusted_rand_score(true_labels, kmeans.labels_)\n",
    "ari_dbscan = adjusted_rand_score(true_labels, dbscan.labels_)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.47"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "round(ari_kmeans, 2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1.0"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "round(ari_dbscan, 2)"
   ]
  }
 ],
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